Volume-04 , Special Issue-03 , May - 2016 Go Back

Data Mining is a way to distillate knowledge from large data sets. Classification consists of predicting a certain outcome based on the given input. Cloud provides the customers to store large amount of data. When classification is done on such large data sets we will know the true potential. But the problem with cloud is that the data is outsourced and anybody can access the data. This has made majority of companies not use the services of cloud. These companies need to give security to customer’s data. One of the ways to provide security to data is by using encryption. But classification cannot be done on encrypted data. This paper addresses the Data Mining over Encrypted Data (DMED) problem. We use the AES and the k-NN classifier to propose a unified framework to provide confidentiality of data.

AES, k-NN classifier, Data Mining over Encrupted Data

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[10] Shivlal Mewada, Sharma Pradeep, Gautam S.S., “Classification of Efficient Symmetric Key Cryptography Algorithms”, International Journal of Computer Science and Information Security (IJCSIS) USA, Vol. 14, No. 2, pp (105-110), Feb 2016 .ISSN: 1947-5500
[11] Shivlal Mewada, Pradeep Sharma, S.S Gautam, “Exploration of Efficient Symmetric AES Algorithm”, Ist IEEE Symposium on Colossal Data Analysis and Networking (CDAN-2016)”, Mar 18th -19th, 2016. ISBN: 978-1-5090-0669-4
[12] B. K. Samanthula, Y. Elmehdwi, and W. Jiang, “k-nearest neighbor classification over semantically secure encrypted relational data,” eprint arXiv:1403.5001, 2014.

VARUN K H and GIRISHA G S, "A Unified Framework for Cloud Computing using AES and k-NN Classifier", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.1-5, 2016.

In spite of the advances in equipment for hand handle gadgets, asset concentrated applications (e.g. video and picture stockpiling and preparing or outline sort) still stay off limits since they require substantial calculation and capacity abilities. Late research has endeavored to address these issues by utilizing remote servers, for example, mists and associate cell phones, for cell phones sent in element systems (i.e., with regular topology changes as a result of hub disappointment or inaccessibility and portability as in a versatile cloud), in any case ,difficulties of unwavering quality and vitality proficiency stay to a great extent unaddressed.to the best of our insight ,we are the first to address these difficulties in a coordinated way for both information stockpiling and handling in versatile cloud. A methodology we get k-out-of-n registering in our answer ,cell phones effectively recover or process information, in the most vitality – proficient route, the length of k out of remote servers are open.

Mobile computing, cloud computing, mobile cloud, energy efficient computing, fault-tolerant.

[1] M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies, “The case for VM-based cloudlets in mobile computing,” IEEE Pervasive Computer., vol. 8, no. 4, pp. 14–23, Oct.-Dec. 2009.
[2] B.-G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, “CloneCloud: Elastic execution between mobile device and cloud,” in Proc. 6th Conf. Computer. Syst., 2011, pp. 301–314.
[3] S. Kosta, A. Aucinas, P. Hui, R. Mortier, and X. Zhang, “ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading,” in Proc. IEEE Conf. Computer. Communication. 2012, pp. 945–953.
[4] C. Shi, V. Lakafosis, M. H. Ammar, and E. W. Zegura, “Serendipity: Enabling remote computing among intermittently connected mobile devices,” in Proc. 13th ACM Int. Symp. Mobile Ad Hoc Network. Computation. 2012, pp. 145–154.
[5] S. M. George, W. Zhou, H. Chenji, M. Won, Y. Lee, A. Pazarloglou, R. Stoleru, and P. Barooah, “DistressNet: A wireless Ad Hoc and sensor network architecture for situation management in disaster response,” IEEE Communication. Mag., vol. 48, no. 3, pp. 128–136, Mar. 2010.
[6] International Journal of Computer Applications (0975 – 8887)Volume 121 – No.19, July 2015
[7] A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centres for cloud computing,” Future Generation Computer. Syst., vol. 28, no. 5, pp. 755–768, 2012.
[8] C. Chen, M. Won, R. Stoleru, and G. Xie, “Resource allocation for energy efficient k-out-of-n system in mobile ad hoc networks,” in Proc. 22nd Int. Conf. Computer Communication Network., 2013, pp. 1–9.
[9] Energy –efficient fault tolerant data storage and processing in mobile cloud 2015

Pushpa S, Sowmya Naik P.T, "Vitality Efficient Fault-Tolerant Data Storage and Dispensation Via K-Out-N Technique in Versatile Cloud", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.6-12, 2016.

Cloud computing provides resources and services to customers in a dynamic basis. That’s why it has become an effective and very efficient way for computing. Profit plays a very important role from perspective of a cloud service provider. This profit will be determined based on how a cloud service platform has been configured and it also depends on market demand. Generally a single long term renting will be used to configure a cloud platform which is not capable of quality service and it also leads to a greater resource waste.

Cloud computing, guaranteed service quality, multiserver system, profit maximization, queuing model, service-level agreement, waiting time.

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Vision, hype, and reality for delivering computing as the 5th utility,” Future Gener. Comp. Sy., vol. 25, no. 6, pp. 599– 616, 2009.
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Raushan kashypa and Sowmya Naik P.T , "Profit Maximization for Cloud Services in Multiserver Environment", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.13-17, 2016.

The responsibility of contemporary multi-core processors is oftentimes bent on by a given power ration that requisite developer to evaluate different resolution trade-offs, e.g., to espouse between many slow, power-efficient cores, or fewer faster, power-hungry cores, or a amalgamation of them . Here, a prototype, a new Hadoop scheduler, called adjudicator, that utilizes aptness proffered by heterogeneous cores within a single multi-core processor for accomplishing a variety of performance objectives. Heterogeneous multi-core processors enable creating virtual resource pools based on “slow” and “fast” cores for multi-class priority scheduling. Since the same data can be accessed with either “slow” or “fast” apertures, spare resources (apertures) can be shared between different resource pools. Using sample experimental data and via simulation, a wrangle is made in approbation of heterogeneous multi-core processors as they achieve “faster” processing of small, interactive MapReduce jobs, while proffering improved throughput for large, batch jobs. Evaluation is done on performance benefits of adjudicator versus the FIFO and Capacity job schedulers that are broadly used in the Hadoop community.

Hadoop, MapReduce, Adjudicator, Job scheduler, Computing, Heterogeneous

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Nishmitha K.S, Megahana K, Monica N, Anima P, Saleem Malik, "Adjudicator: A Pluggable Multiclass Job Scheduler", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.18-23, 2016.

with the prevalence of portable remote gadgets outfitted with different sorts of detecting capacities, another administration worldview named participatory detecting has developed to furnish clients with shiny new background. Be that as it may, the wide use of participatory detecting has its own particular difficulties, among which protection and sight and sound information quality conservations are two basic issues. Shockingly, none of the current work has completely tackled the issue of protection and quality safeguarding participatory detecting with interactive media information. In this paper, we propose SLICER, which is the primary k-unknown protection safeguarding plan for participatory detecting with mixed media information. SLICER coordinates an information coding strategy and message exchange techniques, to accomplish solid insurance of members' protection, while keeping up high information quality. In particular, we consider two sorts of information exchange systems, specifically exchange on get together (TMU) and negligible cost exchange (MCT). For MCT, we propose two diverse however complimentary calculations, including an estimate calculation and a heuristic calculation, subject to various qualities of the necessity. Moreover, we have actualized SLICER and assessed its execution utilizing freely discharged taxi follows. Our assessment results demonstrate that SLICER accomplishes high information quality, with low calculation and correspondence overhead.

Participatory sensing, privacy preservation, K-anonymity, erasure coding

[1] J. Burke, D. Estrin, M. Hansen, A. Parker, N. Ramanathan, S. Reddy, and M. B. Srivastava, “Participatory sensing,” presented at the First Workshop World-Sensor-Web 4th ACM Conf. Embedded Netw. Sen. Syst., Boulder, CO, USA, Oct. 2006.
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[4] M. Mun, S. Reddy, K. Shilton, N. Yau, J. Burke, D. Estrin, M. Hansen, E. Howard, R. West, and P. Boda, “PEIR: The personal environmental impact report, as a platform for participatory sensing systems research,” presented at the 7th Int. Conf. Mobile Syst., Appl., Serv., Krakow, Poland, Jun. 2009.
[5] E. D. Cristofaro and C. Soriente, “Pepsi: Privacy enhancing participatory sensing infrastructure,” presented at the 4th ACM Conf. Wireless Netw. Secur., Hamburg, Germany, Jun. 2011.

Aravinda T V , Naghabhushana , Mamatha O , "Participatory Sensing Systems in Privacy and Quality Preserving Multimedia Data Aggregation", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.24-29, 2016.

The data science is composed of Big Data Analytics (BDA) and Deep Learning (DL). Apart from this Big Data (BD) has got popularity due to its importance in the present genre for both the public and private organizations, as this applies to collection of huge data. Basically, the BD is composed of many national intelligence applications, medical technology, cyber security data, etc. Many of the companies are analyzing the BD for its business purpose. The DL is the sequential or active learning process which collects the complex data and high-level data. This DL has its own beneficial key functions like learning and analysis of the enormous volume of unsupervised data (UD). This performs as the most valuable data analytics tool for BDA. In this paper, a brief overview of Deep learning in Big Data Analytics is presented with the challenges of DL in BD. The statistical survey is formulated by using IEEExplore. Finally, the paper future study requirements in Deep learning are discussed.

Big Data, Big Data Analytics, Deep Learning, Machine Learning, Unsupervised Data

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Leelavathi MV, Sahana Devi K J, "Efficient Deep Learning for Big Data: A Review", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.30-35, 2016.

Online shopping new way of business in present days based on the previous surfing and purchasing products are recommended to the users. The existing method of recommending the product has to undergo several processes or functionalities and these processes or functionalities are manually tested for the accuracy. The manual testing method requires lot of time and money and other resources. To overcome the problem this paper proposes a Automation Testing for the recommender system, with Feature Vector Algorithm and perform a automation on each modules of the Feature Vector algorithm and also checks the Cross-Browser compatibility across the browser and also collecting the online reviews from by using Web Crawling Technique.

Feature Vector, Recommender System, Cross-Browser Compatibility, Web Crawling Technique

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Vinutha K.N, K.S. Sampada, "Survey of Automated Recommender System for Web Applications", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.36-39, 2016.

Successful software is one which provides quality product in given cost and time. Delivering quality software in definite time is a difficult task. Traditional software processes are heavy weight, giving importance to documentation and are rigid making them difficult to apply to different software projects. Agile has become one of the big buzzwords in the software development industry. To put it simply, Agile development or lightweight methods are less documentation oriented and more code oriented stating that source code is the most important document. Agile is a different way of executing software development teams and projects. Agile approaches help the teams respond to unpredictability through incremental, iterative work cadences or otherwise known as “sprints”. Agile methodologies are an alternative to waterfall, or traditional sequential development. This software can be used in development stage, open collaboration and process adaptability in the process of project development. With a minimal work in different stages can improve planning of the project. . This paper discusses a few agile processes, the philosophy driving them and challenges faced while implementing them and mainly focuses on seeking alternative approach to traditional project management.

Agile movement, software methodology, iterative tasks, light-weight methods

[1] Manifesto for Agile software development; http://agilealliance.com
[2] New methodology; Fowler; Martin;
http://www.martinfowler.com/articles/newMethodology.html
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Manjunath R and Nagashree R A, "Agile Software Development", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.40-45, 2016.

In recent years, the need for data collection and Analysis is growing in many scientific disciplines. This is Consequently causing an increase of research in automated data management and data mining to create reliable methods for data analysis. To deal with the need for smart environments and big computational resources, some previous works proposed to address the problem by moving on remote processing, with the aim of sharing supercomputer resources, algorithms and costs. Following this trend, in this work we propose an architecture for advanced remote data processing in a secure, smart and versatile client–server environment that is capable of integrating pre-existing local software. In order to assess the feasibility of our proposal, we developed a case study in the context of an image-based medical diagnostic environment. Our tests demonstrated that the proposed architecture has several benefits: increase of the system throughput, easy upgradability, maintainability and scalability. Moreover, for the scenario we have considered, the system showed a very low transmission overhead which settles on about 2.5%for the widespread 10/100 mbps.

JAAS,DCE-MRI ,OsiriX, secure ,NIST , biomedical ,Image processing ,TLS/SSL

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Manjunath R and Shivarayappa Maranur, "Architecture for remote intelligent data processing", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.46-50, 2016.

When antibiotics were first introduced in the 1940’s, they were hailed as miracle drugs, and quickly provided effective therapy for many of the more dangerous pathogens then prevalent. However, resistance to these antimicrobials developed quickly. The World Health Organisation report into antimicrobial resistance published online, notes that formerly curable bacterial diseases are on the increase. For example, 98% of all South-East Asian gonorrhoea cases are presently multi-drug resistant, while up to 60% of nosocomial infections in the developed world are caused by drug-resistant and often opportunistic pathogens. Infections with rare virulent micro-organisms like Acinetobacter are also on the increase and opportunistic bacterial infections such as Pseudomonas aeruginosa and Salmonella spp. are becoming more common. Several factors contributing to this phenomenon during five decades of antibiotic mishandling have included: health workers misdiagnosing illness or providing the wrong prescription, patients failing to adhere to treatment, and the misuse of antimicrobials in animals with secondary effects observed in humans. To help counteract these problems, advances in technology can be used to hasten the hunt for new drug and vaccine targets. Bioinformatics itself can be defined as utilising large databases of biological information with specific in silico tools to complement traditional wet laboratory-based biology.

Genomes, Putative Target Database, endonuclease fragments,Perl and Bioperl.

[1] Kishore R. Sakharkar, Meena K. Sakharkar and Vincent T. K. Chow, “A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa”
[2] Chan-Eng Chong, Boon-San Lim, Sheila Nathan and Rahmah Mohamed, “In silico analysis of Burkholderia pseudomallei genome sequence for potential drug targets”
[3] Anirban Dutta, Shashi Kr. Singh, Payel Ghosh, Runni Mukherjee, Sayak Mitter and Debashis Bandyopadhyay, “In silico identification of potential therapeutic targets in the human pathogen Helicobacter pylori”
[4] Bhawna Rathi, Aditya N. Sarangi, Nidhi Trivedi, “Genome subtraction for novel target definition in Salmonella typhi”
[5] Gupta Sunil Kumar, Singh Sarita, Gupta Manish Kumar, Pant KK and Seth PK, “Definition of Potential Targets in Mycoplasma pneumoniae Through Subtractive Genome Analysis”
[6] Ren Zhang, Hong-Yu Ou and Chun-Ting Zhang, “DEG: a database of essential genes”.
[7]Debmalya Barh, Anil Kumar, Amarendra Narayana Misra, “Genomic Target Database (GTD): A database of potential targets in human pathogenic bacteria”

Vishwanatha, K S Jagadeesh Muralidhara B K Siddaramappa, "Possible Drug Targets in Human Pathogens", International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.51-53, 2016.